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bert-NER-100
wwwtwwwt/bert-NER-100
bert-NER-100 is a token classification model from wwwtwwwt. Use it when you need labels on individual words, such as names. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Token Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- bert
- Access
- Public
- Created
- Apr 16, 2025
- Updated
- Apr 17, 2025
- SHA
- c4ee4903
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Base models
Datasets
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
bert-NER-100
This model is a fine-tuned version of bert-large-cased on the conll2003 dataset. It achieves the following results on the evaluation set:
- Loss: 0.6481
- Precision: 0.1209
- Recall: 0.0019
- F1: 0.0036
- Accuracy: 0.8331
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 18 | 0.8432 | 0.0 | 0.0 | 0.0 | 0.8325 |
| No log | 2.0 | 36 | 0.6944 | 0.0769 | 0.0003 | 0.0007 | 0.8326 |
| No log | 3.0 | 54 | 0.6481 | 0.1209 | 0.0019 | 0.0036 | 0.8331 |
Framework versions
- Transformers 4.51.1
- Pytorch 2.5.1+cu124
- Datasets 3.5.0
- Tokenizers 0.21.0
- Task
- Token Classification
- Library
- transformers
- Type
- bert
- License
- apache-2.0
- Created
- Apr 16, 2025
- Updated
- Apr 17, 2025